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The design of longitudinal autonomous landing control for a fixed wing Unmanned Aerial vehicle
... Moreover, Hardware-in-Loop simulations are used to validate the efficacy of the designed controller. Similarly, Chen et al. [78] suggested a PID-based longitudinal landing control system for UAVs. The simulations were conducted using MATLAB /Simulink, and the outcomes were good. ...
... The various state estimators utilized in GNC of fixed-wing UAVs are summarised in Table 4. The study of the relevant literature review reveals that many GNC algorithms were developed and proposed without utilizing state estimators [22,[78][79][80][82][83][84]86,[89][90][91][92][93][94][95][96][97][98][99][100][101][102]105,108,109,126], Reviewing the pertinent literature, we find that many GNC algorithms were created and suggested without using state estimators, on the false premise that sensors are always present and free of noise, despite the fact that state estimators are of paramount significance in UAV's GNC algorithm. ...
... MILS was used by the authors of [80,94] to validate the LQR controller's performance in autonomous UAV landing. Similarly, authors of [22,78,[81][82][83][84]89,[91][92][93][98][99][100][101][102][104][105][106][107][109][110][111] performed MILS simulations to simulate their controller's performance. The MILS block diagram is depicted in Figure 3. ...
The pervasive use of unmanned aerial vehicles for both commercial and military operations has undergone rapid development in the recent past. When designing unmanned aerial vehicles, it is highly desirable for them to be able to complete their missions with minimal human intervention. Reaching full autonomy requires a reliable and efficient control algorithm that can handle all flight conditions. Due to the confidential nature of UAV design and development, there is a lack of comprehensive literature on the subject. When it comes to the practical application of the ideas presented in the literature, the situation is even bleaker. This research not only examines the flight phases in which controllers and estimators are used for UAVs but also provides an in-depth analysis of the most recent and state-of-the-art control and estimate techniques for UAVs. Research opportunities and challenges specific to UAVs were also examined in this study in an effort to raise the bar for UAV design as a whole and smooth the way for researchers to go from simulation-based research to practical applications. This review paper establishes a foundation that not only investigates the inherent flight dynamics, control architecture, and Kalman estimators utilized in the development of UAVs but also points out the shortcomings that currently exist in research. A number of design considerations for realistic applications and potential studies are presented in the conclusion.
... Chen et al. [87] suggested a PID-based longitudinal landing control system for UAVs. The simulations were conducted using MATLAB /Simulink, and the outcomes were good. ...
... The study of the relevant literature review reveals that in spite of this area being of most importance, utilization of state estimators has been neglected since many GNC algorithms were developed and proposed without the estimation techniques, assuming that the sensors are available for each and every state and the sensor are totally noise free. Such demonstrations are evident in [27], [87], [88], [90]- [96], [99], [101]- [104], [106]- [110], [112]- [116], [128]. ...
... In this regard, You et al. [116] verified the 8 VOLUME 4, 2016 This article has been accepted for publication in IEEE Access. This is the author's version which has not been fully edited and [92], [94], [95], [89], [87], [27], [96], [114], [117], [91], [118], [97], [98], [99], [101], [102], [103], [104], [105], [107], [108], [109], [110], [88] SILS [106], [139], [140], [44] PILS [116], [141] HILS [93], [115], [26], [139], [140], [142], [143] performance of the controller for the take-off and landing of a fixed-wing UAV. Similarly, Ulker et al. [136] performed PILS for a fixed-wing UAV under windy conditions in various flight scenarios such as level flight, level climb and turn. ...
Unmanned aerial vehicles have evolved rapidly in the recent past for their widespread utilization for both commercial and military purposes. It is extremely desirable while designing unmanned aerial vehicles, to enable them to accomplish their tasks with little human intervention. To achieve full autonomy, an optimal and robust control algorithm that covers complete flight phases is needed. Being propriety in nature, very little information is available in the literature that encompasses all modalities related to UAV design and development. Literature is even more dreath when it comes to near-actual implementation of the developed strategies. This study provides a comprehensive and in-depth review of the most recent and state-of-the-art control and estimation techniques for UAVs, as well as an examination of the flight phases in which those controllers and estimators are utilized. This study also suggests UAV-related research that would improve the overall quality of UAV design and facilitate the transition from software simulations to hardware implementation. Through this paper, a comprehensive platform is established that not only examines the controller and state estimators used for the development of autonomous UAVs but also identifies and discusses the limitations of existing research. In conclusion, several practical implementation considerations and future research directions are proposed.
For the steering engine fault of ducted fan UAV that may arise during the hovering, designing adaptive controller for attitude control. First, concentrating on modeling of the hovering state of ducted fan UAV, and getting the relationship between steering engine and attitude control. Then analyzing the impact of steering engine fault on the attitude control system basing on the control model. Finally, designing model reference adaptive controller basing on the fault model, so that the ducted fan UAV can maintain good attitude control if steering engine fault occurs during the hovering. Simulation results show that when steering engine fault occurs, the model reference adaptive controller can effectively inhibit the adverse effects brought by steering engine fault, so the attitude control system has strong adaptability and robustness.
A flying-wing unmanned aerial vehicle (UAV) landing control problem is studied in this paper, considering the influence of both actual ground effect and atmospheric disturbances. The atmospheric disturbances are the major exterior disturbances for the UAV, and the ground effect imposes extra deviations to aerodynamic parameters. A controller obtained from mixed H2/Hinfin robust control technique is employed to insure the UAV tracks the desired landing trajectory with preferable qualities, even under the influence of uncertainties and disturbances. A conventional controller designed using the classical root locus and bode diagram design method is mentioned either. The two controllers are compared through nonlinear numerical flight simulation. The results indicate that the controller obtained from mixed H2/Hinfin technique provides excellent performance and robustness characteristics than the classical one, especially under the influence of ground effect and atmospheric disturbances.
Free download: http://eprints.gla.ac.uk/3817/1/IEEE3.pdf
Designing and tuning a proportional-integral-derivative (PID) controller appears to be conceptually intuitive, but can be hard in practice, if multiple (and often conflicting) objectives such as short transient and high stability are to be achieved. Usually, initial designs obtained by all means need to be adjusted repeatedly through computer simulations until the closed-loop system performs or compromises as desired. This stimulates the development of "intelligent" tools that can assist engineers to achieve the best overall PID control for the entire operating envelope. This development has further led to the incorporation of some advanced tuning algorithms into PID hardware modules. Corresponding to these developments, this paper presents a modern overview of functionalities and tuning methods in patents, software packages and commercial hardware modules. It is seen that many PID variants have been developed in order to improve transient performance, but standardising and modularising PID control are desired, although challenging. The inclusion of system identification and "intelligent" techniques in software based PID systems helps automate the entire design and tuning process to a useful degree. This should also assist future development of "plug-and-play" PID controllers that are widely applicable and can be set up easily and operate optimally for enhanced productivity, improved quality and reduced maintenance requirements.
Flight dynamics principles [a linear systems approach to aircraft stability and control]
- M Cook
Flight Control Syetem
- Zhang Minglian
Aircraft Control and Simulation. Aircraft Engineering & Aerospace Technology
- F L Lewis
- B L Stevens